Active participation of membrane lipids in inhibition of multidrug transporter P-glycoprotein

P-glycoprotein (Pgp) is a major efflux pump in humans, overexpressed in a variety of cancers and associated with the development of multi-drug resistance. Allosteric modulation by various ligands (e.g., transport substrates, inhibitors, and ATP) has been biochemically shown to directly influence structural dynamics, and thereby, the function of Pgp. However, the molecular details of such effects, particularly with respect to the role and involvement of the surrounding lipids, are not well established. Here, we employ all-atom molecular dynamics (MD) simulations to study the conformational landscape of Pgp in the presence of a high-affinity, third-generation inhibitor, tariquidar, in comparison to the nucleotide-free (APO) and the ATP-bound states, in order to characterize the mechanical effects of the inhibitor that might be of relevance to its blocking mechanism of Pgp. Simulations in a multi-component lipid bilayer show a dynamic equilibrium between open(er) and more closed inward-facing (IF) conformations in the APO state, with binding of ATP shifting the equilibrium towards conformations more prone to ATP hydrolysis and subsequent events in the transport cycle. In the presence of the inhibitor bound to the drug-binding pocket within the transmembrane domain (TMD), Pgp samples more open IF conformations, and the nucleotide binding domains (NBDs) become highly dynamic. Interestingly, and reproduced in multiple independent simulations, the inhibitor is observed to facilitate recruitment of lipid molecules into the Pgp lumen through the two proposed drug-entry portals, where the lipid head groups from the cytoplasmic leaflet penetrate into and, in some cases, translocate inside the TMD, while the lipid tails remain extended into the bulk lipid environment. These “wedge” lipids likely enhance the inhibitor-induced conformational restriction of the TMD leading to the differential modulation of coupling pathways observed with the NBDs downstream. We suggest a novel inhibitory mechanism for tariquidar, and potentially for related third-generation Pgp inhibitors, where lipids are seen to enhance the inhibitory role in the catalytic cycle of membrane transporters.

Lipid invasion of P-glycoprotein, enhanced by binding of an inhibitor.     

Predicting bioactive conformations and binding modes of macrocycles

Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein–protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.     

Conformational and docking studies of acyl homoserine lactones as a robust method to investigate bioactive conformations

A method aiming at investigating possible bioactive conformations of acyl homoserine lactone (AHL) quorum sensing (QS) modulators is established. The method relies on the exhaustive conformational analysis of AHLs by varying torsion angles around the amide group then on the selection of the closest conformation to those known from co-crystallized XRD data of AHL-receptor complexes. These latter are then docked as rigid ligand within the receptor binding site, leading to interactions with binding site residues which are highly consistent as compared with the data arising from XRD studies. The method is first validated using AHLs for which XRD data of their complexes with their cognate receptor are available, then extended to examples for which the binding mode is still unknown.Three compounds were used to validate the method: hexanoyl homoserine lactone (HHL) as an example of autoinducer, 3-oxo-butanoyl homoserine lactone (OBHL), as a representative model of 3-oxo-AHLs, and 4-(4-chlorophenoxy)butanoyl homoserine lactone (CPOBHL) as an example of a QS inhibitor. The conformational analysis of these three compounds to their cognate protein (TraR, SdiA, LasR and CviR) provides the data which enable the next rigid docking step. Further rigid docking of the closest conformations compared to the known bioactive ones within the binding sites allows to recover the expected binding mode with high precision (atomic RMSD < 2 Å). This “conformational analysis/torsion angle filter/rigid ligand docking” method was then used for investigating three non-natural AHL-type QS inhibitors without known co-crystallized XRD structures, namely was 2-hexenoyl homoserine lactone (HenHL), 3-oxo-4-phenylbutanoyl homoserine lactone (OPBHL) and 3-(4-bromophenyl)propanoyl homoserine lactone (BPPHL). Results provide insights into their possible binding mode by identifying specific interactions with some key residues within the receptor binding site, allowing discussion of their biological activity.     

蛋白质分子与配体结合过程构象变化的研究

蛋白质分子与配体的作用模式主要有直接的环区结合及铰链式结合两种方式。针对这两种不同的作用方式,我们提出采用不同的策略进行结合过程的构象研究。对于直接的环区结合模式,通过建立环区主链构象库,来实现蛋白质环区与配体的准柔性对接,并以链霉抗生物素蛋白体系为例对构象库建立的可行性进行了验证计算。对铰链结合方式,采用分步对接的方法进行计算,并具体应用于HIV蛋白酶与其小分子配体的结合过程。计算结果表明,这两种处理方法分别能较好地模拟不同类型的蛋白质与配体结合的的构象变化。     

Computational study of the dynamics of mannose disaccharides free in solution and bound to the potent anti-HIV virucidal protein cyanovirin

In this paper, we present a computational study of the dynamics of the potent anti-HIV virucidal protein cyanovirin in complex with mannose disaccharides. Recently, it has been experimentally demonstrated that cyanovirin binds mannose oligomers on the surface of glycoprotein gp120. gp120, a protein on the surface of the HIV virus, is key in the process of viral docking and transfer of genetic material into human cells. Cyanovirin prevents the transfer of viral RNA into human cells. In this study, we found that, among all residues that show nuclear Overhauser effects in the solution NMR experiments, residues Glu41 and Arg76 appear to interact with the sugar at the high-affinity binding site through stronger Coulombic interactions. In particular, Arg76 participates in a dynamical mechanism that caps and locks the sugar once it is bound to the protein. We also studied the distribution of glycosidic torsional angles of mannose disaccharides in solution and compared it with those when bound at the high- and low-affinity sites of the protein. Throughout our 20 ns simulations, we find that the sugar bound to the high-affinity site preserves the most favorable conformation in solution while the sugar bound at the low-affinity site does not. The sugar at the low-affinity site can adopt both conformations, but we find it most predominantly on the one that is least probable for the free sugar in solution. We also carried out a detailed study of the interactions between the disaccharides and different amino acids as well as between the disaccharide and the solvent at both binding locations.     

Conformational selection of protein kinase A revealed by flexible-ligand flexible-protein docking

Protein kinases have high structural plasticity: their structure can change significantly, depending on what ligands are bound to them. Rigid-protein docking methods are not capable of describing such effects. Here, we present a new flexible-ligand flexible-protein docking model in which the protein can adopt conformations between two extremes observed experimentally. The model utilized a molecular dynamics-based simulated annealing cycling protocol and a distance-dependent dielectric model to perform docking. By testing this model on docking four diverse ligands to protein kinase A, we found that the ligands were able to dock successfully to the protein with the proper conformations of the protein induced. By imposing relatively soft conformational restraints to the protein during docking, this model reduced computational costs yet permitted essential conformational changes that were essential for these inhibitors to dock properly to the protein. For example, without adequate movement of the glycine-rich loop, it was difficult for the ligands to move from the surface of the protein to the binding site. In addition, these simulations called for better ways to compare simulation results with experiment other than using the popular root-mean-square deviation between the structure of a ligand in a docking pose and that in experiment because the structure of the protein also changed. In this work, we also calculated the correlation coefficient between protein-ligand/protein-protein distances in the docking structure and those in the crystal structure to check how well a ligand docked into the binding site of the protein and whether the proper conformation of the protein was induced.     

Conformational analysis of TMC114, a novel HIV-1 protease inhibitor

TMC114, a potent novel HIV-1 protease inhibitor, remains active against a broad spectrum of mutant viruses. In order to bind to a variety of mutants, the compound needs to make strong, preferably backbone, interactions and have enough conformational flexibility to adapt to the changing geometry of the active site. The conformational analysis of TMC114 in the gas phase yielded 43 conformers in which five types of intramolecular H-bond interactions could be observed. All 43 conformers were subject to both rigid and flexible ligand docking in the wild-type and a triple mutant (L63P/V82T/I84V) of HIV-1 protease. The largest binding energy was calculated for the conformations that are close to the conformation observed in the X-ray complexes of TMC114 and HIV-1 protease.     

T-Analyst: a program for efficient analysis of protein conformational changes by torsion angles

T-Analyst is a user-friendly computer program for analyzing trajectories from molecular modeling. Instead of using Cartesian coordinates for protein conformational analysis, T-Analyst is based on internal bond-angle-torsion coordinates in which internal torsion angle movements, such as side-chain rotations, can be easily detected. The program computes entropy and automatically detects and corrects angle periodicity to produce accurate rotameric states of dihedrals. It also clusters multiple conformations and detects dihedral rotations that contribute hinge-like motions. Correlated motions between selected dihedrals can also be observed from the correlation map. T-Analyst focuses on showing changes in protein flexibility between different states and selecting representative protein conformations for molecular docking studies. The program is provided with instructions and full source code in Perl.     

Studies on the Conformations and Hydrogen Bonding of ACE Inhibitory Tripeptide VEF by All-atom Molecular Dynamics Simulations and Molecular Docking

Molecular dynamic simulations and molecular docking are performed to study the conformations and hydrogen bonding interactions of ACE inhibitory tripeptide VEF. Intramolecular distance, radius of gyration, solvent-accessible surface, and root-mean-square deviations are used to characterize the properties of VEF in aqueous solution. The VEF molecule is highly flexible in water and conformations can shift between the extended and folded states. The VEF molecule exists in extended state mostly in aqueous solution and the conformations bonded with ACE are also the extended ones. The findings indicate that MD simulations have a good agreement with the molecular docking analysis.     

基于3D-药效团的P糖蛋白和细胞色素P4503A4的协同作用机理研究

P糖蛋白(P-glycoprotein,Pgp)和细胞色素P4503A4(CYP3A4)是决定药物ADME性质的两个重要蛋白,目前还无法通过实验方法,从分子水平清晰阐明这两个蛋白采取怎样的互补作用机理来降低外来药物的生物利用度.通过3D-药效团模建方法,提取Pgp和CYP3A4的共同底物的特征阐明这两个蛋白可能的协同作用模式.所得的药效团有助于理解药物分子同这两个蛋白的作用模式,同时该模型可以指导新药设计和改造,从而提高药物的生物利用度.     

Significance analysis and multiple pharmacophore models for differentiating P-glycoprotein substrates

P-glycoprotein (Pgp) mediated drug efflux affects the absorption, distribution, and clearance of a broad structural variety of drugs. Early assessment of the potential of compounds to interact with Pgp can aid in the selection and optimization of drug candidates. To differentiate nonsubstrates from substrates of Pgp, a robust predictive pharmacophore model was targeted in a supervised analysis of three-dimensional (3D) pharmacophores from 163 published compounds. A comprehensive set of pharmacophores has been generated from conformers of whole molecules of both substrates and nonsubstrates of P-glycoprotein. Four-point 3D pharmacophores were employed to increase the amount of shape information and resolution, including the ability to distinguish chirality. A novel algorithm of the pharmacophore-specific t-statistic was applied to the actual structure-activity data and 400 sets of artificial data (sampled by decorrelating the structure and Pgp efflux activity). The optimal size of the significant pharmacophore set was determined through this analysis. A simple classification tree using nine distinct pharmacophores was constructed to distinguish nonsubstrates from substrates of Pgp. An overall accuracy of 87.7% was achieved for the training set and 87.6% for the external independent test set. Furthermore, each of nine pharmacophores can be independently utilized as an accurate marker for potential Pgp substrates.     

Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach

Ligand docking to flexible protein molecules can be efficiently carried out through ensemble docking to multiple protein conformations, either from experimental X-ray structures or from in silico simulations. The success of ensemble docking often requires the careful selection of complementary protein conformations, through docking and scoring of known co-crystallized ligands. False positives, in which a ligand in a wrong pose achieves a better docking score than that of native pose, arise as additional protein conformations are added. In the current study, we developed a new ligand-biased ensemble receptor docking method and composite scoring function which combine the use of ligand-based atomic property field (APF) method with receptor structure-based docking. This method helps us to correctly dock 30 out of 36 ligands presented by the D3R docking challenge. For the six mis-docked ligands, the cognate receptor structures prove to be too different from the 40 available experimental Pocketome conformations used for docking and could be identified only by receptor sampling beyond experimentally explored conformational subspace.     

Differences in Sensitivity to UVC, UVB and UVA Radiation of a Multidrug-Resistant Cell Line Overexpressing P-Glycoprotein

Multidrug resistance (MDR) is the phenomenon in which cultured tumor cells, selected for resistance to one chemotherapeutic agent, simultaneously acquire resistance to several apparently unrelated drugs. The MDR phenotype is multifactorial. The best-studied mechanism involves the expression of a membrane protein that acts as an energy-dependent efflux pump, known as P-glycoprotein (Pgp), capable of extruding toxic materials from the cell. In this work, resistance to UVA radiation, but not to UVC nor UVB, was observed in an MDR leukemia cell line. This cell line overexpresses Pgp. To study the role of Pgp in the resistance to UVA radiation, two MDR modulators or reversing agents (verapamil and cyclosporin A) capable of blocking Pgp activity were used. Cell viability was assessed and the techniques of flow cytometry and fluorescence microscopy were employed to measure the extrusion of rhodamine 123 by the efflux pump. The results show that MDR modulators did not modify the resistance to UVA radiation. Furthermore, although cell viability was not significantly altered, Pgp function was impaired after UVA treatment, suggesting that this glycoprotein may be a physical target for oxidative damage, and that other factors may be responsible for the UVA resistance. In agreement with this, it was found that the resistant cell line presented a higher catalase activity than the parental (non-MDR) cell line.     

Binding of naproxen to bovine serum albumin and tryptophan-modified bovine serum albumin

Two classes of binding sites, a single high-affinity site with an association constant of 4·8×10⁶ M⁻¹ and two low-affinity sites with association constant of about 0·05×10⁶ M⁻¹ have been observed in the interaction of Naproxen with bovine serum albumin (BSA). Chemical modification of two tryptophan residues in BSA with 2-hydroxy-5-nitrobenzyl bromide has led to a reduction in the association constant of the high-affinity site by 89% and its number of binding sites by 66% suggesting the involvement of tryptophan residues in the high-affinity site. In contrast, the two low-affinity sites were not affected by the modification. Binding of Naproxen to the low-affinity sites of BSA induces microdisorganisation of the albumin structure leading to conformational changes as evident from fluorescence measurements with 1-anilino-8-naphthalenesulphonic acid as the probe.     

Structural Characterization of O‐ and C‐Glycosylating Variants of the Landomycin Glycosyltransferase LanGT2

The structures of the O‐glycosyltransferase LanGT2 and the engineered, C? C bond‐forming variant LanGT2S8Ac show how the replacement of a single loop can change the functionality of the enzyme. Crystal structures of the enzymes in complex with a nonhydrolyzable nucleotide‐sugar analogue revealed that there is a conformational transition to create the binding sites for the aglycon substrate. This induced‐fit transition was explored by molecular docking experiments with various aglycon substrates.     

Molecular modelling prediction of ligand binding site flexibility

We have investigated the efficacy of generating multiple sidechain conformations using a rotamer library in order to find the experimentally observed ligand binding site conformation of a protein in the presence of a bound ligand. We made use of a recently published algorithm that performs an exhaustive conformational search using a rotamer library to enumerate all possible sidechain conformations in a binding site. This approach was applied to a dataset of proteins whose structures were determined by X-ray and NMR methods. All chosen proteins had two or more structures, generally involving different bound ligands. By taking one of these structures as a reference, we were able in most cases to successfully reproduce the experimentally determined conformations of the other structures, as well as to suggest alternative low-energy conformations of the binding site. In those few cases where this procedure failed, we observed that the bound ligand had induced a high-energy conformation of the binding site. These results suggest that for most proteins that exhibit limited backbone motion, ligands tend to bind to low energy conformations of their binding sites. Our results also reveal that it is possible in most cases to use a rotamer search-based approach to predict alternative low-energy protein binding site conformations that can be used by different ligands. This opens the possibility of incorporating alternative binding site conformations to improve the efficacy of docking and structure-based drug design algorithms.     

Targeting the conformational transitions of MDM2 and MDMX: insights into dissimilarities and similarities of p53 recognition

MDM2 and MDMX are oncogenic homologue proteins that regulate the activity and stability of p53, a tumor suppressor protein involved in more than 50% of human cancers. While the large body of experiments so far accumulated has validated MDM2 as a therapeutically important target for the development of anticancer drugs, it is only recently that MDMX has also become an attractive target for the treatment of tumor cells expressing wild type p53. The availability of structural information of the N-terminal domain of MDM2 in complex with p53-derived peptides and inhibitors, and the very recent disclosure of the crystal structure of the N-terminal domain of MDMX bound to a p53 peptide, offer an unprecedented opportunity to provide insight into the molecular basis of p53 recognition and the identification of discriminating features affecting the binding of the tumor suppressor protein at MDM2 and MDMX. By using coarse graining simulations, in this study we report the exploration of the conformational transitions featured in the pathway leading from the apo-MDM2 and apo-MDMX states to the p53-bound MDM2 and p53-bound MDMX states, respectively. The results have enabled us to identify a pool of diverse conformational states of the oncogenic proteins that affect the binding of p53 and the presence of conserved and non-conserved interactions along the conformational transition pathway that may be exploited in the design of selective and dual modulators of MDM2 and MDMX activity.     

A normal mode-based geometric simulation approach for exploring biologically relevant conformational transitions in proteins

A three-step approach for multiscale modeling of protein conformational changes is presented that incorporates information about preferred directions of protein motions into a geometric simulation algorithm. The first two steps are based on a rigid cluster normal-mode analysis (RCNMA). Low-frequency normal modes are used in the third step (NMSim) to extend the recently introduced idea of constrained geometric simulations of diffusive motions in proteins by biasing backbone motions of the protein, whereas side-chain motions are biased toward favorable rotamer states. The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. When applied to a data set of proteins with experimentally observed conformational changes, conformational variabilities are reproduced very well for 4 out of 5 proteins that show domain motions, with correlation coefficients r > 0.70 and as high as r = 0.92 in the case of adenylate kinase. In 7 out of 8 cases, NMSim simulations starting from unbound structures are able to sample conformations that are similar (root-mean-square deviation = 1.0-3.1 ?) to ligand bound conformations. An NMSim generated pathway of conformational change of adenylate kinase correctly describes the sequence of domain closing. The NMSim approach is a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or as starting points for more sophisticated sampling techniques.     

Docking-undocking combination applied to the D3R Grand Challenge 2015

Novel methods for drug discovery are constantly under development and independent exercises to test and validate them for different goals are extremely useful. The drug discovery data resource (D3R) Grand Challenge 2015 offers an excellent opportunity as an external assessment and validation experiment for Computer-Aided Drug Discovery methods. The challenge comprises two protein targets and prediction tests: binding mode and ligand ranking. We have faced both of them with the same strategy: pharmacophore-guided docking followed by dynamic undocking (a new method tested experimentally here) and, where possible, critical assessment of the results based on pre-existing information. In spite of using methods that are qualitative in nature, our results for binding mode and ligand ranking were amongst the best on Hsp90. Results for MAP4K4 were less positive and we track the different performance across systems to the level of previous knowledge about accessible conformational states. We conclude that docking is quite effective if supplemented by dynamic undocking and empirical information (e.g. binding hot spots, productive protein conformations). This setup is well suited for virtual screening, a frequent application that was not explicitly tested in this edition of the D3R Grand Challenge 2015. Protein flexibility remains as the main cause for hard failures.     

Structural mining: self-consistent design on flexible protein-peptide docking and transferable binding affinity potential

A flexible protein-peptide docking method has been designed to consider not only ligand flexibility but also the flexibility of the protein. The method is based on a Monte Carlo annealing process. Simulations with a distance root-mean-square (dRMS) virtual energy function revealed that the flexibility of protein side chains was as important as ligand flexibility for successful protein-peptide docking. On the basis of mean field theory, a transferable potential was designed to evaluate distance-dependent protein-ligand interactions and atomic solvation energies. The potential parameters were developed using a self-consistent process based on only 10 known complex structures. The effectiveness of each intermediate potential was judged on the basis of a Z score, approximating the gap between the energy of the native complex and the average energy of a decoy set. The Z score was determined using experimentally determined native structures and decoys generated by docking with the intermediate potentials. Using 6600 generated decoys and the Z score optimization criterion proposed in this work, the developed potential yielded an acceptable correlation of R(2) = 0.77, with binding free energies determined for known MHC I complexes (Class I Major Histocompatibility protein HLA-A(*)0201) which were not present in the training set. Test docking on 25 complexes further revealed a significant correlation between energy and dRMS, important for identifying native-like conformations. The near-native structures always belonged to one of the conformational classes with lower predicted binding energy. The lowest energy docked conformations are generally associated with near-native conformations, less than 3.0 Angstrom dRMS (and in many cases less than 1.0 Angstrom) from the experimentally determined structures.